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    Home / Central Data Catalog / WLD_2020_PFC_V01_M / variable [V17]
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Predicting Food Crises 2020, Dataset for reproducing working paper results

Afghanistan, Burkina Faso, Chad...and 18 more, 2007 - 2020
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Reference ID
WLD_2020_PFC_v01_M
Producer(s)
Bo Pieter Johannes Andree, Andres Chamorro, Aart Kraay, Phoebe Spencer, Dieter Wang
Metadata
DDI/XML JSON
Created on
Sep 16, 2021
Last modified
Sep 16, 2021
Page views
3265
Downloads
108
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  • predicting_food_crises_data

Rainfall Estimates from Rain Gauge and Satellite Observations (CHIRPS) - Mean (rain_mean)

Data file: predicting_food_crises_data

Overview

Valid: 183596
Invalid: 0
Minimum: 0
Maximum: 125.927
Type: Continuous
Decimal: 0
Width: 9
Range: 0 - 125.927200317383
Format: Numeric

Description

Definition
CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring. CHIRPS data is available at 5 and 10 day accumulations.
Source of information
CHIRPS Pentad, processed in Google Earth Engine). Cropland mask (GFSAD), pasture mask (FAO - FGGD)

Others

Notes
Frequency: Raw images (5-day) are aggregated to the monthly level using the average value. Monthly images are summarized to the district level using the average value.
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